Last week saw a wonderful conference held by the the Dutch network for qualitative research KWALON, based at the Erasmus University, Rotterdam. The theme was no less than the future of Qualitative Data Analysis (QDA) software.
Chair Jeanine Evers opened the session by outlining 8 important themes the group had identified on qualitative analysis software.
The first was the challenge of adding features to software that is requested by users or present in competitors software, without breaking the underlying design of the software. Quirkos really connects to this theme, because we have always tried to have a very simple tool-set, based on a philosophy that the software should be very easy to use. While we obviously take heed of suggestions made by our users, we actually have a comprehensive and limited set of features which we have always planned to introduce, and will continue delivering these over the next few years.
However, it is not the intention of Quirkos to become a large software package with lots of features, something Jeanine described as a ‘obese software’ that needs to be put on a diet. It was noted that many software providers have released ‘lite’ versions of their software, and another discussion point was if this fragmented approach can benefit universities and users.
User friendliness was another theme of the session, and by keeping Quirkos simple we hope to always have this at the fore of our design philosophy. In my talk (you can now get the slides here) I discussed these themes as mostly being about improving accessibility. To this end, we have tried to make Quirkos not just easier to use, but also to teach and own, with permanent licences and discounts for researchers from countries that can’t usually afford this type of software. For us, the long-term goal is not just increasing the number of people that use software for qualitative analysis, but the number that are able to take up qualitative research in general.
There was also some good discussion at the end of our talk about the risks of making software easy to use: especially that it also makes it easy to use badly. As we’ve discussed many times on this blog, software in general can make it very satisfying to code, and this can appear to be more productive than stepping back and thinking about themes or a undertaking deep readings of the data. These problems can apply to all software packages, so it is important that students and educators work together to learn about the whole analysis procedure, and what part CAQDAS can play.
Comments also touched on how memo making is a critical part of a good iterative and reflexive qualitative analysis process: which at the moment Quirkos doesn’t forefront (see for example how F4analyse and a future version of Cassandre will operate). Although it is possible to record memos by typing in a source, which gives you the ability to tag and code your memos, as well as writing notes as source properties, this is currently not highlighted enough and we plan on revamping the memo features in a future update.
The final theme of the conference, and a major push, was to promote a standard way to exchange software between qualitative software. At the moment it is very difficult for users to move their coded data from one software package to the other. Although most major packages provide options to export their data to other formats (such as spreadsheet CSV data like Quirkos), there is currently no single standard for how should be formatted, so it is very difficult to bring this data – complete with themes and coding - into another package.
This is very important: but not just for users of different of qualitative analysis software, who want to be able to collaborate with universities and colleagues who use different packages. It’s also important for archival purposes, so that qualitative coded data can be universally shared and stored for secondary analysis, and to make it easier for data to be brought in for analysis from the huge number of digital sources in the digital humanities, such as history, journalism, and social media. Such a standard could also be important for formatting data so that machine learning and natural language processing can automate some of the simpler analysis processes on very large ‘big-data’ datasets.
So there is a lot to be done, but a lot of interest in the area in the next few years, with major and minor players all taking different approaches, and seeking common ground. Quirkos is honoured to be a small part of this, and will do whatever we can to improve the world of qualitative analysis for this and the next generation of researchers.